InsNet-CRAFTY v1.0: Understanding future policy interventions and decision making using Large Language Models

Climb-Forest partners at KIT are researching how Large Language Models (LLMs) can simulate the behaviour of policy actors within institutional networks. Their work explores how these actors adjust policy instruments to meet multiple policy targets and how such decisions shape land use dynamics.

Read this article to find out more about their work and the exciting InsNet-CRAFTY (Institutional Network – Competition for Resources between Agent Functional Types) v1.0 a multi-LLM-agent model with a polycentric institutional framework coupled with an agent-based land system model.